Description
Leader of the group Stochastics: Bert Zwart.
Many natural and man-made systems and processes are driven by random phenomena. Examples can be found in areas such as communication, energy, information, logistics, and transportation systems. In order to model, describe, and improve such systems, our group develops and studies probabilistic, operational and statistical models. Our group’s analysis of these models relies on techniques from fundamental probability theory, queueing theory, stochastic scheduling, spatial stochastics and stochastic geometry. Our work with various companies in these areas, as well as with top researchers and universities across the globe, ensures our position at the forefront of every aspect of this research field.
Vacancies
Two talented PhD students, on the subject of “Machine Learning for Combatting Cybercrime"
Two talented PhD students, on the subject of “Machine Learning for Combatting Cybercrime”. Over the past few years, cybercrime has increased dramatically and has become a major threat to the proper functioning of our modern society. This has raised the need for the development of new and powerful methods to combat cybercrime.
News
Health Innovation Seed Fund III B.V. invests in Stokhos emergency mathematics
CWI spin-off company Stokhos Emergency Mathematics receives an investment of Health Innovation Seed Fund III. With this financial injection Stokhos aims to further optimize its software called Seconds, to achieve a scale-up and further international expansion.
CWI researchers make power grid more reliable with mathematics
Researchers from Centrum Wiskunde & Informatica (CWI) discovered how large fluctuations in solar and wind energy, combined with the physical network dynamics of electricity, can cause failures in power grids.
Bart Kamphorst finds best possible scheduling policy for servers in information-scarce settings
Nobody fancies a long wait between requesting some kind of online service and actually receiving that service. Therefore, in many situations, ICT-specialists aim to design their servers in such a way that their customers are served in an efficient manner. Research of CWI PhD-student Bart Kamphorst contributes a number of performance analyses of blind algorithms and moreover identifies a blind algorithm that is in some sense optimal.
More efficient ambulance planning with new mathematical models
In serious life-threatening situations a fast ambulance response is required. Late arrivals can have a serious impact on the well-being of the patients and can also have consequences regarding policy making. In practice, providing a fast ambulance response time is not always possible. PhD candidate Martin van Buuren of CWI has developed mathematical models that can help to realize fast response times.
Members
Associated Members
Publications
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Kleinrouweler, J.W.M. (2020, October 28). Modeling and optimization of network assisted video streaming.
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Mahfoud, M, Bernasco, W, Bhulai, S, & van der Mei, R.D. (2020). Forecasting spatio‑temporal variation in residential burglary with the integrated Laplace approximation framework: Effects of crime generators, street networks, and prior crimes. Journal of Quantitative Criminology, 1–28. doi:10.1007/s10940-020-09469-3
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Usanov, D. (2020, May 11). Emergency response networks: dynamic dispatching and relocation of resources.
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Nesti, T. (2020, March 30). Stochastic analysis of energy networks.
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Saxena, M, Kapodistria, S, & Núñez Queija, R. (2020). Perturbation analysis of two queues with random time-limited polling. In Queueing Theory and Network Applications.
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Berkhout, J, Pauwels, E.J.E.M, van der Mei, R.D, Stolze, J, & Broersen, S. (2020). Short-term production scheduling with non-triangular sequence-dependent setup times and shifting production bottlenecks. International Journal of Production Research. doi:10.1080/00207543.2019.1705420
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Koch, T, Knapen, L, & Dugundji, E.R. (2019). Path complexity and bicyclist route choice set quality assessment. Personal and Ubiquitous Computing. doi:10.1007/s00779-019-01350-w
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Chen, B. (2019, December 11). Heavy tails : asymptotics, algorithms, applications.
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Zweers, B.G, Bhulai, S, & van der Mei, R.D. (2019). Optimizing pre-processing and relocation moves in the Stochastic Container Relocation Problem. European Journal of Operational Research. doi:10.1016/j.ejor.2019.11.067
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Bazhba, M, Blanchet, J, Rhee, C.H, & Zwart, A.P. (2019). Queue length asymptotics for the multiple-server queue with heavy-tailed Weibull service times. Queueing Systems, 93(3-4), 195–226. doi:10.1007/s11134-019-09640-z
Current projects with external funding
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Ontwikkeling van Data Analytics, Data Science en Crypto Analyse technieken ()
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Impactstudie Noord/Zuidlijn Gemeente Amsterdam
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Samenwerkingsovereenkomst Stichting 113 / CWI - Zelfmoordpreventie
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Data-driven optimization for a vital elderly care system in the Netherlands (DOLCE VITA)
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Dynamic urban traffic flow management using floating-car, planning, and infrastructure data (Dynafloat)
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Lane Analysis & Route Advisor (LARA)
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Evidence-based effective monitoring and control of Covid-19 after the initial outbreak (None)
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Het dectecteren van (corona-gerelateerde) problemen bij de hulpvragers van 113 Zelfmoordpreventie voor en de uitbraak van de coronapandamie in Nederland middels state-of-the-art Natural Language Processing (NLP) (None)
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State estimation for spatio-temporal point processes with applications to criminology (None)
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PPS Engie
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Robust, Effective and Adaptable Ship Designs for Uncertain Transition Paths (READINESS)
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Urban Mobility Observatory (UMO)
Related partners
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De Verkeersonderneming
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Gemeente Amsterdam
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RIVM
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Stichting 113
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Universiteit Wageningen
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Academisch Medisch Centrum
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Stichting Sensor City
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Engie Services West Nederland B.V.
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Erasmus Universiteit Rotterdam
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Leids Universitair Mediach Centrum
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Technische Universiteit Eindhoven
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Technische Universiteit Delft
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Universiteit Utrecht
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Vrije Universiteit Amsterdam